2022
PCfun: a hybrid computational framework for systematic characterization of protein complex function
Sharma V, Fossati A, Ciuffa R, Buljan M, Williams E, Chen Z, Shao W, Pedrioli P, Purcell A, Martínez M, Song J, Manica M, Aebersold R, Li C. PCfun: a hybrid computational framework for systematic characterization of protein complex function. Briefings In Bioinformatics 2022, 23: bbac239. PMID: 35724564, PMCID: PMC9310514, DOI: 10.1093/bib/bbac239.Peer-Reviewed Original ResearchConceptsProtein complex functionGO termsProtein complex databasesGene Ontology (GONatural language processing techniquesRandom forestLanguage processing techniquesNearest neighborsProtein complexesSystematic annotationCellular statesBiological functionsBiological processesQuery vectorComplex queriesWord vectorsUnsupervised approachSupervised approachChild termsProteinMolecular biologySubunit compositionComplex databasesComplex functionsComputational framework
2012
Quantitative modeling of the terminal differentiation of B cells and mechanisms of lymphomagenesis
Martínez M, Corradin A, Klein U, Álvarez M, Toffolo G, di Camillo B, Califano A, Stolovitzky G. Quantitative modeling of the terminal differentiation of B cells and mechanisms of lymphomagenesis. Proceedings Of The National Academy Of Sciences Of The United States Of America 2012, 109: 2672-2677. PMID: 22308355, PMCID: PMC3289327, DOI: 10.1073/pnas.1113019109.Peer-Reviewed Original ResearchConceptsB-cell exitTranscriptional regulatory modulesTerminal differentiationTerminal differentiation of B cellsSelf-regulatory interactionsGene expression profiling dataMechanisms of lymphomagenesisExpression profiling dataMature human B cellsRegulatory modulesGene regulationT cell signalingB cellsCellular statesDifferentiation of B cellsHuman B cellsGerminal centersTumorigenic alterationsGenesQuantitative kinetic modelMemory B cellsAssociated with lymphomagenesisFeedback loopLymphomagenesisT cells